The Time for Value

{ Euclidean Q4 2015 Letter }

We believe that now is a very attractive time to invest in value strategies. Following similar times in the past, value investors achieved both strong absolute returns and robust relative performance versus the broad market indexes. In this letter, we explore what history can teach us about what is to come. We also review Euclidean’s investment approach to explain how we are positioned to capitalize on this opportunity.

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Our confidence in Euclidean’s investment philosophy comes from using machine learning to study the history of public companies and their market values. Over the past 50 years, abundant evidence shows that it would have been fruitful to buy companies that were priced very low in relation to their earnings. Moreover, our own research suggests that this has particularly been the case for companies that also have a combination of consistent operations, good returns on capital, and balance sheet strength. This is why we formed Euclidean: to oversee a systematic process that seeks to invest in good companies at very low prices.

However, during recent years, Euclidean’s returns have been below market averages. As discussed in prior communications, these results have come during an extended period of growth stocks outperforming their out-of-favor value counterparts. In this context, the S&P 500’s performance has been driven by a small number of companies. The index’s two best performers of 2015 were Amazon (+118%) and Netflix (+134%), with price-to-earnings ratios of approximately 900 and 300, respectively. Given that the lower of these valuation multiples is almost 25 times more expensive than the average Euclidean holding, it is no surprise that we have missed these recent gains.

There are other unusual – and unsustainable – aspects of this current market. Joel Greenblatt, a prominent member of the “buy good companies at good prices” school of investing, shared the following observations in a September 2015 note to investors [1]:

Buying only those companies that lose money has earned investors anywhere from 20% to 50% over the last twelve months.

This is the first time since the late 1990s that over 80% of IPOs are losing money.

Buying the top momentum stocks and shorting the bottom momentum stocks (from the Morgan Stanley momentum index) would have achieved positive 18% returns so far this year whereas buying the top value stocks and shorting the bottom value stocks (from the Morgan Stanley value index) would have lost 13%.

These observations should give all investors pause. If you have not been participating in the market’s recent gains, should you pivot your investment process based on what has recently worked in the markets? Here are three reasons why we believe the answer is no:

Companies derive their intrinsic value from their ability to generate cash. It is, therefore, speculative to invest in companies that have not yet demonstrated an ability to consistently deliver earnings.

Across long periods, abundant evidence suggests that getting the most earning power for your dollar has been the key to investment success.

Following periods when buying companies on sale (#2 above) has fallen out of favor, value strategies have consistently reasserted themselves through strong absolute and relative performance. We hope to clearly illustrate this point in the charts that follow.

Let’s dig into these points to understand why we believe now is the time to add capital to value strategies.

Refresher on the long-term performance of simple systematic approaches to value investing

Last year, we shared with you the simulated results below, which show the annualized performance by decade of four simple value-oriented approaches for selecting equity investments. [2]

The results are compelling. The simulations reflect investing in inexpensive companies, where inexpensiveness means being among the cheapest 10% of all companies as ranked by a respective value factor. Clearly, a good route to realizing above-average returns would have been adhering to a process — even a very simple one — for buying companies at low prices in relation to their sales, book values, or earnings.

Yet, as we will see, achieving these returns over the long run requires enduring periods where buying inexpensive companies does not yield good results.

Market Cycles

Although value investing has performed well over the long term, it is also clear that it has not performed well all of the time. The charts that follow represent one of the most widely researched approaches to value investing, where a value stock is defined as one having high book equity to market equity. We will look through two lenses at the cycles value investors have endured along the way to superior returns. The first relates to how value investing has performed versus the S&P 500 market index. The second relates to how it has done versus growth stock investing.

Value vs. the S&P 500 Index

Since 1962 [3], a hypothetical portfolio based on this value approach [4] would have grown almost 10 times more than the same money invested in the S&P 500. Yet, while this form of value investing would have done exceptionally well over the long run, it has performed poorly during recent years. So, perhaps the right question is: does value investing still work?

You might have asked that same question in 1966, 1973, 1980, 1991, 1999, 2003, and 2009. At those times, the same value approach behind the returns described above would have underperformed the S&P 500 for multiple years, in some cases by more than 30%. This chart illustrates this point. The top section shows the hypothetical cumulative returns of the value approach versus the S&P 500 total return (i.e., price appreciation plus dividends) between 1962 and September 2015. The bottom part of the chart shows the drawdowns of the value approach relative to the S&P 500. [5]

Clearly, value investing has endured many long periods of underperformance despite its long-term success. In fact, we are currently in the midst of such a period. But what happens when these periods end? To answer that question, we plotted the two-year hypothetical return of this value strategy starting from the bottom of the six largest relative drawdowns experienced prior to the current one.

While it may seem obvious that the relative returns of this value strategy might be strong once its relative performance turned around, the charts also show that strong absolute returns have been realized in each value recovery.

Value vs. Growth Investing

The prior charts show how value investing has performed versus the S&P 500 market index. The graphs that follow examine the cycles involved in buying inexpensive (VALUE) companies versus expensive (GROWTH) companies. We shared this analysis earlier this year and have updated it with data through November. We believe this lens remains particularly relevant, as we are currently in the midst of the longest period of growth stock dominance since World War II.

The returns above [6] reflect the trailing five-year annualized return of a hypothetical portfolio (the value vs. growth portfolio) that goes up when value stocks are outperforming growth stocks and down when growth is outperforming value. In this case, we look at the relative performance of the 20% least expensive (VALUE) companies in relation to the 20% most expensive (GROWTH) companies. All returns are compounded monthly.

The chart shows that value outperforms growth across most five-year periods. In fact, it does so by roughly 5% annualized over time. However, since World War II, there have been six distinct periods when growth outperformed value on a trailing five-year compounded return basis. We are currently in one of these periods, with the prior one occurring during the dot-com era.

Therefore, it is of great interest to examine how value has previously performed following similar times in the past. This chart provides a perspective.

During the previous five periods when growth outperformed value, value subsequently delivered very strong results over the subsequent 5+ years. In the current cycle, the value rebound has not yet occurred.

Cycles – Takeaways

In both cases, as we examine value investing in relation to growth stocks and to the S&P 500 index, we hope you take away three things:

The periodic underperformance of value strategies has not erased their superior results over the long term.

When value strategies endure a period of underperformance, they have subsequently delivered very strong absolute and relative returns.

That value investing has done well over time, but hasn’t worked all of the time, reflects an important point. Periods of underperformance make value strategies difficult to stick with. If value investing was both fruitful and easy, more would embrace it, and the opportunity to do well with value strategies would be competed away.

It is worth pondering this third statement. It reminds us of a famous Steve Jobs quote on what separates successful and unsuccessful entrepreneurs:

“I'm convinced that about half of what separates the successful entrepreneurs from the non-successful ones is pure perseverance.”

We believe the same could be said of value investors. The superior long-term returns offered by value strategies would have accrued only to investors with the conviction to persevere across difficult periods. Why would it be any different today?

How These Studies Relate to Our Investment Process

Years ago, we caught our first glimpse of the insights presented earlier in this letter, and they made us wonder: if the discipline of adhering to simple rules for investing in inexpensive companies would have done well across long periods in the past, might there be an opportunity to do even better by taking a deeper look at companies’ fundamentals? This led us to start Euclidean. We wanted a process-driven approach, informed by these sorts of lessons from history, for investing our own money.

As we set off on this adventure, we focused on seeking timeless lessons regarding how to tell if one company is inherently more valuable than another. We also searched for historical context about the prices you can safely pay for a given company when seeking to compound wealth over long periods.

As we pursued this wisdom, we found it helpful to imagine how an exceptional investor might evaluate a potential investment. After becoming familiar with how a company serves customers, manages expenses, and deploys capital, we felt this investor would compare the company with his experiences involving similar investments from the past. To the extent that those analogs, or “comparables,” in the past had done well, we suspected that his confidence in the new opportunity would be high, and the opposite would also be true.

It became clear to us that this investor’s success must come from being exceptional in three respects. The first one is obvious – he must accumulate a significant number of meaningful experiences on which to rely on when making decisions. Next, he must distill the right lessons from a lifetime of experience that was surely peppered with red herrings – for example, foolish investments that luckily worked out and instances when sound application of his expertise led to losses. Lastly, he would need a high level of discipline to avoid deviating from a robust investment process seeped in his historical experiences, particularly given the frequency with which his investments would underperform the market and more speculative forms of investing.

With this image in mind, we aspired to emulate these qualities of our exceptional investor through data. We knew from our own experiences building a business that how well a company serves customers, manages expenses, and deploys capital is reflected in its financial statements. So, our first step was to use machine-learning technologies to digest the financial statements and investment outcomes of public companies going back many years.

This gave us a basis for evaluating today’s equity investment options in light of how similar opportunities in the past actually performed. This step also showed that the historical record is full of support for the notion that there are persistent principles for evaluating companies and estimating the prices at which they tend to make good long-term investments. These principles are easy to understand and, characterized by findings such as “all else being equal, lower prices are better than higher prices”, are grounded in common sense.

Our next steps were to develop an infrastructure for overseeing a systematic application of these principles. And, as we anticipated that the pendulum of history would expose us to periods of challenging performance, to commit to adhering to this process through thick and thin.

Thus, we continue to maintain and establish holdings in good companies at attractive prices. Because of the relative attractiveness of our portfolio, as highlighted on the following page, and the context of how value and growth investing cycles have worked over time, we expect to deliver attractive long-term results to Euclidean’s investors.

[2] In the simulations, Standard & Poor’s COMPUSTAT database was used as a source for all information about companies and securities for the entire simulated time period. The S&P 500 return is the total return of the S&P 500, which refers to the Standard & Poor's 500 Index with dividends reinvested. Simulated returns also include the reinvestment of all income. In each simulation, NYSE, AMEX, and NASDAQ companies were ranked according to the stated criteria such as Market Value to Book Value. Non-US-based companies, companies in the financials sector, and companies with a market capitalization that, when adjusted by the S&P500 Index Price to January 2010, is less than $400M were excluded from the ranking.

The simulation results reflect assets-under-management (AUM) at the start of each month that, when adjusted by the S&P 500 Index Price to January 2010, is equal to $100M. Portfolios were constructed by investing equal amounts of capital in the top decile of companies represented by each value factor and then rebalancing monthly to equally weight the evolving constituents of the top decile. The amount of shares of a security bought or sold in a month was limited to no more than 10% of the monthly volume for a security. During the period 1983 to present, the purchase and sale price of a security was based on volume weighted daily closing price of the security during the first ten trading days of each month. Prior to 1983, when daily pricing is not available for all securities, the purchase and sale price of a security was based on the monthly closing price of the security. Transaction costs are factored as $0.02 per share plus an additional slippage factor that increases as a square of the simulation’s volume participation in a security. Specifically, if participating at the maximum 10% of monthly volume, the simulation buys at 1% more than the average market price or, conversely, sells at 1% less than the average market price.

Other than these transaction costs, the simulated results do not reflect the deduction of any management fees or expenses. Historical simulated results presented herein are for illustrative purposes only and are not based on actual performance results. Historical simulated results are not indicative of future performance.

[3] Although the S&P 500 Index was formed in 1957, we began this analysis in 1962 because the S&P 500 Total Return data in Compustat is not available prior to that year.

[4] The historical results represented herein are for illustrative purposes only and are not based on actual performance results. The hypothetical portfolio and the associated returns do not reflect the effect of transaction costs, bid/ask spreads, slippage, or management fees. Historical results are not indicative of future performance. Kenneth French’s website archives maintain many time series of returns related to fundamental investing. One such monthly time series represents the returns of ten portfolios formed by sorting the universe by each stock’s ratio of book equity to market value and splitting them evenly into deciles. The weight of each stock in each portfolio is proportional to the stock’s market value. In our analysis, we use the portfolio with the highest book equity to market value as the “value approach.” The specific file for these returns can be found here. In this analysis, the S&P 500’s total returns (market appreciation plus dividends) were computed using data from Standard and Poor’s COMPUSTAT database.

[5] We construct the drawdowns of the value approach relative to the S&P 500 as follows. We form a time series by subtracting the monthly S&P 500 total returns from the monthly value approach returns. This time series represents a hypothetical fund that has bought long the value approach and sold short the S&P 500. When the value approach outperforms the S&P 500, this hypothetical fund goes up, and when the opposite happens, it goes down. Therefore, a drawdown of this hypothetical fund represents a period where the value approach is underperforming the S&P 500.

[6] Historical results represented herein are for illustrative purposes only and are not based on actual performance results. The hypothetical portfolio and the associated returns do not reflect the effect of transaction costs, bid/ask spreads, slippage, or management fees. Historical results are not indicative of future performance.

All results and the analysis described in the above post exclusively used data obtained from Kenneth R. French’s research data library. To construct the hypothetical set of returns herein, we used this particular data file. This dataset contains the returns of 25 portfolios. The portfolios, which are constructed at the end of each June, represent the intersections of five portfolios formed on size (market equity, ME) and five portfolios formed on the ratio of book equity to market equity (BE/ME).

In our analysis, we constructed a hypothetical portfolio (the value vs. growth portfolio) that goes up when value stocks are outperforming growth stocks and goes down when growth stocks are outperforming value stocks. We calculated the monthly returns for the value vs. growth portfolio to be equal to the average of the five high BE/ME portfolios minus the average of the five low BE/ME portfolios in the dataset referenced above. All returns in our analysis are compounded monthly.

We share these numbers because they are easy-to-communicate measures that show the results of our systematic process for buying shares in historically sound companies when their earnings are on sale. [7] [8]

It is important to note that Euclidean uses similar concepts but different measures to assess individual companies as potential investments. Our models look at certain metrics over longer periods and seek to understand their volatility and rate of growth. Our process also makes a series of adjustments to company financial statements that our research has found to more accurately assess results, makes complex trade-offs between measures, and so on. These numbers should, however, give you a sense of what you own as a Euclidean Investor. In general, higher numbers for these measures are more attractive. The key measures are:

Earnings Yield – This measures how inexpensive a company is in relation to its demonstrated ability to generate cash for its owners. A company with twice the earnings yield as another is half as expensive; therefore, all else being equal, we seek companies with very high Earnings Yields. Earnings Yield reflects a company’s past four-year average earnings before interest and tax, divided by its current enterprise value (enterprise value = market value + debt – cash).

Return on Capital – This measures how well a company has historically generated cash for its owners in relation to how much capital has been invested (equity and long-term debt) in the business. At its highest level, this measure reflects two important things. First, it is an indicator of whether a company’s business is efficient at deploying capital in a way that generates additional income for its shareholders. Second, it indicates whether management has good discipline in deciding what to do with the cash it generates. For example, all else being equal, companies that overpay for acquisitions, or retain more capital than they can productively deploy, will show lower returns on capital than businesses that do the opposite. Return on Capital reflects a company’s four-year average earnings before interest and tax, divided by its current equity + long-term debt.

Equity / Assets – This measures how much of a company’s assets can be claimed by its common shareholders versus being claimed by others. High numbers here imply that the company owns a large portion of its figurative “house” and, all else being equal, indicates a better readiness to weather tough times.

Revenue Growth Rate – This is the annualized rate a company has grown over the past four years.

[7] All Euclidean measures are formed by summing the values of Euclidean’s pro-rata share of each portfolio company’s financials. That is, if Euclidean owns 1% of a company’s shares, it first calculates 1% of that company’s market value, revenue, debt, assets, earnings, and so on. Then, it sums those numbers with its pro-rata share of all other portfolio companies. This provides the total revenue, assets, earnings, etc. across the portfolio that are used to calculate the portfolio’s aggregate measures presented here.

[8] The S&P 500 measures are calculated in a similar way as described above. The market values, revenue, debt, assets, earnings, etc., for each company in the S&P 500 are added together. Those aggregate numbers are then used to calculate the metrics above. For example, the earnings yield of the S&P 500 is calculated as the total average four-year earnings before interest and taxes across all 500 companies divided by those companies’ collective enterprise values (all 500 companies’ market values + cash – debt).

Euclidean’s Ten Largest Holdings as of December 31, 2015

We provide this information because many of you have expressed an interest in talking through individual positions as a means of better understanding how our investment process seeks value.

We are available to discuss these holdings with you at your convenience. We are happy to explain both why our models have found these companies to be attractive as well as our sense of why the market has been pessimistic about their future prospects.

Euclidean’s ten largest positions as of December 31, 2015 (in alphabetical order) [9]

Applied Industrial Technologies – AIT

Arrow Electronics – ARW

Ensign Group – ENSG

Matrix Service Co – MTRX

PC Connection – PCCC

Preformed Line Products – PLPC

Primoris Services Corp – PRIM

Sanderson Farms – SAFM

Stepan Company – SCL

Synnex Corp – SNX

[9] There is no assurance that any securities discussed herein will remain in the Fund at the time you receive this report or that securities sold have not been repurchased. It should not be assumed that any of the securities transactions, holdings or sectors discussed were or will be profitable, or that the investment recommendations or decisions Euclidean makes in the future will be profitable or equal the performance of the securities discussed herein. There is no assurance that any securities, sectors or industries discussed herein will be included in or excluded from the Fund’s holdings.

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